Some web sites and other types of interactive systems implement recommendation services for generating personalized recommendations of items stored or represented in a data repository. One common application for recommendation services involves recommending products for purchase, rental, subscription, viewing or some other form of consumption. For example, some e-commerce web sites provide services for recommending products to users based on their respective purchase histories, rental histories, product viewing histories, or item ratings. Recommendation services are also used to recommend web sites, news articles, users, music and video files, and other types of items.
Some recommendation systems operate by using collected event histories of users to generate recommendation rules that associate particular items with other items. These rules are then used to generate personalized recommendations for users. As one example, if a relatively large number of users who purchase item A also purchase item B, a recommendation rule may be generated that associates item A with item B. This rule may then be used as a basis for recommending item B to users who purchase, view, favorably rate, or otherwise express an interest in item A. The recommendation system may also generate and use recommendation rules that are based on more complex associations (e.g., “users who search for X tend to view Y,” or “users who purchase A and B tend to purchase C.”).